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Snowflake Data ArchitectRole Overview

We are seeking an experienced Snowflake Data Architect to design, develop, and govern scalable, secure, and high-performing cloud data platforms. The ideal candidate will have strong expertise in Snowflake, data architecture, cloud technologies, data modelling, and modern data engineering practices.

The Snowflake Data Architect will work closely with data engineers, analysts, business stakeholders, and technology teams to define data architecture strategies and deliver robust data solutions that support analytics, reporting, data science, and business intelligence initiatives.

Key ResponsibilitiesDesign and implement scalable, secure, and high-performance data architectures using Snowflake.Define enterprise data architecture, data models, data flows, integration patterns, and technology standards.Develop conceptual, logical, and physical data models aligned with business and analytical requirements.Design Snowflake databases, schemas, tables, views, stages, streams, tasks, and other platform components.Define and implement data ingestion and integration patterns for batch and real-time data.Develop and optimise ELT/ETL pipelines integrating data from a variety of source systems.Establish best practices for Snowflake performance optimisation, workload management, storage, and compute utilisation.Design security and access-control frameworks, including roles, privileges, data masking, row-level security, and other governance capabilities.Define data governance, metadata management, data quality, lineage, and lifecycle management practices.Support data migration and modernisation initiatives, including migration from legacy data warehouses and on-premises platforms to Snowflake.Evaluate and recommend appropriate Snowflake features and cloud technologies based on business and technical requirements.Collaborate with data engineering teams to establish development, deployment, and operational standards.Contribute to CI/CD, DevOps, automation, and infrastructure-as-code practices for data platforms.Troubleshoot complex architectural, performance, scalability, and data integration issues.Produce and maintain architecture documentation, standards, design patterns, and technical specifications.Provide technical leadership and mentoring to data engineers and other technical team members.Stay current with developments in Snowflake, cloud data platforms, data engineering, and modern data architecture.Required Skills and ExperienceStrong experience designing and implementing enterprise-scale data platforms.Extensive hands-on experience with Snowflake and its architecture.Strong understanding of data warehousing, dimensional modelling, data lakes, data lakehouses, and modern cloud data architectures.Experience with SQL and database technologies.Strong understanding of ETL/ELT concepts and data integration patterns.Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.Knowledge of data security, governance, privacy, and access-control principles.Experience with data modelling tools and techniques.Understanding of distributed data processing and large-scale data environments.Experience working with APIs, databases, files, streaming platforms, and other data sources.Familiarity with data engineering and orchestration technologies such as dbt, Apache Airflow, Azure Data Factory, AWS Glue, or similar tools.Experience with source control, CI/CD, and DevOps practices.Strong analytical, problem-solving, and communication skills.Ability to translate business requirements into scalable technical architecture.Desirable SkillsSnowflake certifications or relevant cloud certifications.Experience with Snowflake features such as Snowpipe, Snowpipe Streaming, Streams, Tasks, Dynamic Tables, Snowpark, and Secure Data Sharing.Experience implementing data mesh, data fabric, or lakehouse architectures.Experience with real-time/streaming technologies such as Kafka.Experience with dbt and modern analytics engineering practices.Knowledge of data cataloguing

GCS is acting as an Employment Business in relation to this vacancy.

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Senior AWS Big Data Architect (Cloud Data Platforms & Streaming Analytics)

Location: Chicago
Work Arrangement: Hybrid
Employment Type: Contract

Overview

We are seeking a highly specialized AWS Big Data Architect to lead the design and implementation of enterprise-scale cloud data platforms and real-time analytics solutions. This role requires deep expertise across AWS data services, distributed processing frameworks, streaming technologies, and large-scale data architecture.

The ideal candidate will have extensive experience building modern lakehouse architectures, optimizing high-volume ETL pipelines, and enabling scalable analytics and machine learning workloads within cloud-native environments.

Key Responsibilities

Architect and implement scalable big data solutions on AWSDesign modern data lake and lakehouse architecturesBuild and optimize real-time and batch data processing pipelinesLead cloud migration and modernization initiatives for enterprise data platformsDesign streaming data solutions using Kafka and AWS-native streaming servicesDevelop scalable ETL/ELT frameworks and data orchestration workflowsDefine data governance, security, and compliance standardsCollaborate with engineering, analytics, and platform teams on enterprise data strategiesOptimize performance, cost, scalability, and resiliency across data environmentsProvide architectural leadership and technical mentorship

Required Technical Skills

10+ years of experience in data engineering and architecture5+ years designing enterprise-scale AWS big data solutionsDeep expertise with AWS services including:EMRGlueRedshiftAthenaKinesisLambdaS3IAMLake FormationStrong experience with:Apache SparkHadoop ecosystemKafkaAirflowDatabricksExperience designing:Data lakesLakehouse architecturesReal-time streaming platformsEvent-driven architecturesStrong SQL and Python/Scala development skillsExpertise with infrastructure automation:TerraformCloudFormationExperience implementing data governance and security best practicesStrong understanding of distributed systems and high-volume data processing

Preferred Qualifications

Experience supporting ML/AI data platformsKnowledge of Delta Lake, Iceberg, or HudiExperience with observability and monitoring frameworksBackground supporting enterprise analytics or customer data platformsAWS Certified Solutions Architect or AWS Data Analytics certification

Nice to Have

Telecom, media, or large enterprise environment experienceExposure to containerized data platforms using KubernetesExperience with FinOps and cloud cost optimization strategies

GCS is acting as an Employment Business in relation to this vacancy.

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